Absolute CD4+ T-lymphocyte and CD34+ stem cell counts by single-platform flow cytometry: the way forward

Area of Science:

• Immunophenotyping
• Flow Cytometry
• Cell Enumeration

Background:

• Accurate enumeration of CD4+ T lymphocytes and CD34+ stem cells is critical for clinical trials and patient management.
• Current methods involve dual-platform technology, which can exhibit significant inter-laboratory variability.
• The UK NEQAS for Leucocyte Immunophenotyping provides a benchmark for assessing laboratory performance.

Purpose of the Study:

• To evaluate the performance advantage of single-platform technology over dual-platform methods for cell enumeration.
• To compare the inter-laboratory variability of different single-platform approaches.
• To determine if single-platform technology improves quality control for CD4+ T lymphocyte and CD34+ stem cell counts.

Main Methods:

• Analysis of data from UK NEQAS for Leucocyte Immunophenotyping schemes.
• Comparison of inter-laboratory coefficients of variation (CVs) for CD4+ T lymphocyte and CD34+ stem cell counts obtained by single-platform and dual-platform methodologies.
• Subgroup analysis of different single-platform techniques (FlowCount, TruCount, volumetric).

Main Results:

• Single-platform technology consistently yielded lower inter-laboratory CVs for CD4+ T lymphocyte counts (mean 13.7%) compared to dual-platform methods (mean 23.4%).
• Among single-platform approaches, the volumetric method showed the lowest mean CV (7.1%), followed by TruCount (13%) and FlowCount (17.2%).
• Single-platform methods for CD34+ stem cell enumeration also demonstrated lower inter-laboratory CVs (mean 18.6%) than dual-platform technology (mean 28.6%).

Conclusions:

• Single-platform technology is advantageous for the absolute enumeration of CD4+ T lymphocytes and CD34+ stem cells.
• Adoption of single-platform technology is recommended to enhance the quality control of multi-centre clinical trial data.
• Standardized single-platform approaches can significantly reduce variability in cell subset enumeration.